GA Flood Risk & Social Vulnerability

An Exploration of County & Census Tract Impacts

Shikha Srinivas, Community Resilience Data Intern, Re:Public; Justin Cross, Data Science Intern, Re:Public; Max Evans, Head of Product and Geospatial Data, Re:Public

This virtual link is meant to supplement Re:Public’s poster at the 2021 Georgia Climate Conference. It contains interactive graphics which included screencaps on the poster as well as a few additional charts.

The datasets used include the National Flood Hazard Layer for a 100-year flood by extent (2018), the CDC’s Social Vulnerability Index (2018), and Re:Public’s database of flooded community lifelines (accessed December 2020).

Flood Claims in GA

Number of flood claims by tract:

County Flooding and SVI

The following interactive map shows the CDC’s SVI overall vulnerability percentile (ranked at the national level) by county.

The following scatterplot shows how overall vulnerability (percentiles taken at the national level) compares to county area flooded.

The interactive map below shows county and percent flooding by land area.

The following interactive map shows the percent of community lifelines (critical infrastructure) in the floodplain of a 100-year flood by county.

The following maps show impacted lifelines by type and county for the top 5 most well-defined community lifelines in FEMA’s dataset.

Land Area and Lifelines Flooding Relationship

Using Re-Public community lifeline flooding data at the county level, we wanted to assess the relationships between land area flooded and lifeline flooding.

There is little correlation between the two parameters (R^2 = 0.08651). While some of the coastal counties face very flood risk by land area, inland counties with high social vulnerability (ex. Colquitt) may deal with a large loss of critical infrastructure.

Tract Flooding & SVI

The interactive map displays social vulnerability of every tract (ranked at the state level).

The following plot shows tract-level land area flooding.

This plot shows the relative population affected (using % flooding as the proportion for population affected).

For every tract, we calculated a combined social vulnerability-flooding score by multiplying the vulnerability percentile (ranked at the state level) with the tract flooding. ``

This graphic shows the scores from the overall vulnerability percentile.